Demand Forecasting for Shopify: A Practical Guide for Store Owners

Demand forecasting is predicting how much of each product you will sell over a future period. Done well, it tells you what to order, how much to order, and when to place the order so stock arrives before you run out.

Done badly (or not at all), it leads to two expensive problems: stockouts on your best sellers and overstock on everything else.

Shopify does not include demand forecasting in its native tools. The recently retired Stocky app had basic forecasting, but it was widely regarded as unreliable, and it is shutting down entirely in August 2026. So if you want to forecast demand for your Shopify store, you need to build a process yourself or use a dedicated tool.

Here is a practical guide to getting started.

Why forecasting matters for Shopify merchants

Forecasting might sound like something only large retailers need. But the smaller your business, the more a single bad purchasing decision hurts.

If you over-order a product, you tie up cash that could have been spent on marketing or faster-selling inventory. If you under-order, you stock out and lose sales. Research suggests that 69% of online shoppers will buy from a competitor when their preferred item is unavailable. You do not get most of those customers back.

Forecasting helps you:

Buy the right quantities. No more guessing whether to order 100 or 500 units. Base your purchasing on projected demand.

Time your orders correctly. Account for supplier lead times so stock arrives before you run out, but not so early that it sits idle.

Plan for seasonality. If you sell seasonal products, forecasting helps you ramp up before peak periods and reduce orders before demand drops.

Manage cash flow. Forecasting turns inventory purchasing from a series of reactive decisions into a planned budget.

The simple approach: moving averages

You do not need machine learning or a data science background to forecast demand. The simplest approach that actually works is a moving average.

Here is how:

Step 1: Pull your sales history. Export product-level sales data from Shopify for the last 3-6 months (longer is better if you have it).

Step 2: Calculate average daily sales. For each product, divide total units sold by the number of days in the period. If you sold 300 units over 90 days, your average daily demand is about 3.3 units.

Step 3: Project forward. Multiply your average daily demand by the number of days you want to forecast. For a 30-day forecast: 3.3 x 30 = about 100 units.

Step 4: Factor in lead time. If your supplier needs 14 days to deliver, you need to order at least 14 days before you expect to run out. Your reorder point is: daily demand x lead time = 3.3 x 14 = about 47 units. When stock hits 47 units, it is time to reorder.

Step 5: Add a safety buffer. Demand is not perfectly consistent. Add 10-20% to your reorder point as safety stock to account for variability. So your practical reorder point becomes about 52-56 units.

This approach will not win any awards for sophistication, but it is dramatically better than guessing.

Accounting for seasonality

The moving average approach works well for products with stable demand but falls apart for seasonal items. If you sell Christmas decorations, your average daily sales over 12 months will be wildly misleading.

For seasonal products, you need to look at the same period from the previous year (or years) rather than a rolling average. Compare this March to last March, not to the last 90 days.

This is where Shopify's 180-day data limitation becomes a real problem. If you can only see six months of history, you cannot compare year-over-year patterns. You need either your own historical records or a tool that captures longer-term data.

Stockful captures daily inventory snapshots for up to a year, giving you the historical baseline that seasonal forecasting requires.

Common forecasting mistakes

Forecasting from stock-out periods. If a product was out of stock for two weeks last month, your average daily sales for that month are artificially low. You did not have zero demand during those two weeks; you had zero supply. Adjust your calculations to exclude (or estimate demand during) stockout periods.

Ignoring lead time variability. Your supplier says 14 days, but sometimes it is 10 and sometimes it is 21. Use the longest realistic lead time for your reorder calculations, not the optimistic estimate.

Treating all products the same. Your A items (top revenue drivers) deserve more careful forecasting than your C items. Invest your time where the financial impact is greatest.

Not reviewing forecasts against actuals. Forecasting is an iterative process. After each order cycle, compare what you predicted to what actually sold. Adjust your method based on where the forecast was off.

Over-relying on automation. Automated forecasting tools are helpful, but they cannot account for things like an upcoming promotion, a competitor going out of stock, or a product going viral on social media. Always layer human judgement on top of the numbers.

When to invest in a forecasting tool

The manual approach works for stores with a small number of SKUs and relatively stable demand. You will outgrow it when:

You have more than 50-100 active SKUs. Manually forecasting each product becomes impractical.

Your products have different demand patterns (seasonal, trending, stable). A single method does not fit all of them.

You are making purchasing decisions weekly or more frequently. The manual process cannot keep up.

You sell across multiple locations and need per-location forecasts.

At that point, look for a tool that connects to your Shopify data, calculates forecasts automatically, and provides reorder recommendations. The best tools combine historical sales data with current stock levels and supplier lead times to give you specific, actionable guidance on what to buy and when.

Start simple, improve over time

The goal of forecasting is not perfection. It is being less wrong than you were when you were guessing. Even a simple moving average will improve your purchasing decisions over intuition alone.

Start with your top 10-20 products (your A items from ABC analysis). Forecast demand for the next 30 days. Place your orders based on the forecast instead of gut feeling. Compare results. Refine.

Forecasting is a skill that gets better with practice. The important thing is to start.

Further reading

• What Is Inventory Velocity and Why It Matters
• Shopify Inventory Tracking: Why 180 Days Isn't Enough
• How to Use ABC Analysis to Prioritize Your Shopify Inventory
• Shopify Inventory Tracking with Stockful
• Shopify Inventory Management with Stockful

Stockful's reorder report combines your sales velocity, current stock levels, and supplier lead times to recommend what to buy and when. Get started free at [stockful.app](https://stockful.app).